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Software Engineering Prof. Dr. Bertrand Meyer March 2007 – June 2007 Chair of Software Engineering Software development: “Process” vs “agile” with material by Marco Piccioni

Software Engineering Prof. Dr. Bertrand Meyer March 2007 – June 2007 Chair of Software Engineering Software development: “Process” vs “agile” with material

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Software EngineeringProf. Dr. Bertrand Meyer

March 2007 – June 2007

Chair of Software Engineering

Software development:“Process” vs “agile”

with material by Marco Piccioni

Software Engineering, lecture 8: Process vs Agile 2

Three cultures of software development

Three cultures:

Process

Agile

Object

The first two are usually seen as exclusive, but all have major contributions to make

Software Engineering, lecture 8: Process vs Agile 3

Process-oriented

(Sometimes called formal )Examples:

Waterfall model (from 1970 on) Military standards CMM, then CMMI ISO 9000 series of standards Rational Unified Process (RUP) Cluster model

Overall idea: to enforce a strong engineering discipline on the software development process Controllability, manageability Traceability Reproducibility

Software Engineering, lecture 8: Process vs Agile 4

Agile

Extreme Programming (XP)Lean ProgrammingTest-Driven Development (TDD)Scrum

Software Engineering, lecture 8: Process vs Agile 5

This lecture (today and tomorrow)

1. The case for agile methods 2. Process-oriented methods 3. Towards a combination

Software Engineering, lecture 8: Process vs Agile 6

- 1 -

The case foragile methods

(or: the Cubicle Strikes Back)

Software Engineering, lecture 8: Process vs Agile 7

“The agile manifesto”

We are uncovering better ways of developing software by doing it and helping others do it.

Through this work we have come to value:

Individuals and interactions over processes and tools

Working software over comprehensive documentation

Customer collaboration over contract negotiation Responding to change over following a plan

That is, while there is value in the items on the right, we value the items on the left more.

agilemanifesto.org

Software Engineering, lecture 8: Process vs Agile 8

Scheme 1: predictable manufacturing

Assembly-line production is possible: Define specifications and constructions steps Build some instances and perform

measurements On the basis of that experience, estimate &

schedule future production

Software Engineering, lecture 8: Process vs Agile 9

Scheme 2: new model development

Each model specific, evolving process: Requirements change between races

Static reasons (specific tracks) Dynamic reasons (weather, competitors)

High level of competition Continuous experimenting

Prototypes rather than products

Software Engineering, lecture 8: Process vs Agile 10

Assembly-line vs prototype

Assembly-line manufacturing

Prototype-style manufacturing

Specify, then build Hard to freeze specifications

Reliable effort and cost estimates are possible, early on

Estimates only become possible late, as empirical data emerge

Can identify schedule and order all activities

Activities emerge as part of the process

Stable environment Many parameters change; need creative adaptation to change

C. Larman Agile & Iterative Development A Manager guide Addison Wesley 2003

Software Engineering, lecture 8: Process vs Agile 11

What about software?

In the agile view, most software development is not a predictable, mass-manufacturing problem, but falls under the new product development model

Software Engineering, lecture 8: Process vs Agile 12

Agile methods: basic concepts

Principles:Iterative developmentCustomer involvementSupport for changePrimacy of codeSelf-organizing teamsTechnical excellenceSearch for simplicity

Practices: Evolutionary

requirements Customer on site User stories Pair programming Design & code standards Test-driven development Continuous refactoring Continuous integration Timeboxing Risk-driven development Daily tracking Servant-style manager

Shunned: “big upfront requirements”; plans; binding documents; diagrams (e.g. UML); non-deliverable products

Software Engineering, lecture 8: Process vs Agile 13

Another view: lean programming

Eliminate waste Minimize inventory Maximize flow Pull from demand Empower workers Meet customer requirements Do it right the first time Abolish local optimization Partner with suppliers Create a culture of continuous

improvement

Mary Poppendieck*

*See www.poppendieck.com

“Documentation that is not part of the final

program”

Iterative development

Decide as late as possible

Build in tests;build in changeFret about

value, not scope

Software Engineering, lecture 8: Process vs Agile 14

Manager’s role in agile development

The manager does not: Create a work

breakdown structure, schedule or estimates

Tell people what to do (usually)

Define and assign detailed team roles

The manager does provide: Coaching Service and leadership Resources Vision Removal of impediments Promotion of agile

principles

Software Engineering, lecture 8: Process vs Agile 15

Iterative development

Each iteration is a self-contained mini-project

Iteration goal: a release, that is a stable, integrated and tested partially complete system

All software across all teams is integrated into a release each iteration

Most iteration releases are internal

During each iteration, there should be no changes from external stakeholders

Software Engineering, lecture 8: Process vs Agile 16

Iterative development

Not a new idea (see Microsoft’s Daily Build, cluster model)

Avoid “big bang” effect of earlier approaches

Short iteration cycles

Software Engineering, lecture 8: Process vs Agile 17

The waterfall modelFeasibility

study

Requirements

Specification

Globaldesign

Detaileddesign

Implemen-tation

Distribution

V & V

Software Engineering, lecture 8: Process vs Agile 18

Waterfall risk profile

Requirements Design Implementation Integration, V&V…

Time

Po

ten

tial

imp

act

of r

isk

bei

ng

tac

kled

C. Larman Agile & Iterative Development A Manager guide Addison Wesley 2003 p. 58

Software Engineering, lecture 8: Process vs Agile 19

Risk-driven vs. client-driven planning

What would you choose to implement first?

The riskiest, most difficult tasks…or

What the client perceives as his highest business value?

Software Engineering, lecture 8: Process vs Agile 20

Timeboxed iterative development

Set iteration end date, no change permitted

If requests cannot be met within timebox:

Place lower priority requests back on wish list Never move a deadline Never ask developers to work more to meet a deadline

Iterations may typically last from 1 to 6 weeks

Software Engineering, lecture 8: Process vs Agile 21

Parkinson’s law*

Work expands so as to fill the time available for its completion

*C. Northcote Parkinson: Parkinson's Law, or The Pursuit of Progress, 1957

Software Engineering, lecture 8: Process vs Agile 22

Arguments for timeboxing

For developers: More focus (to limit Parkinson’s law) Forced to tackle small levels of complexity

For managers: Early forcing difficult decisions and trade-offs Better skill assessment of people involved and

better balance and optimization providedFor stakeholders:

They see the actual progress of the application every iteration end

Software Engineering, lecture 8: Process vs Agile 23

Arguments against upfront requirements

Details are too complex for people to grasp Stakeholders are not sure what they want They have difficulty stating it Many details will only be revealed during

development As they see the product develop, stakeholders will

change their minds External forces cause changes and extensions

(e.g. competition)

Software Engineering, lecture 8: Process vs Agile 24

Requirements uncertainty

Jones C. 1997 Applied Software Measurement MCGraw Hill

0

5

10

15

20

25

30

35

Requirements change

10 100 1000 10000

Project size in FP

Software Engineering, lecture 8: Process vs Agile 25

Actual use of requested features

Never: 45%Seldom: 19%Occasionally: 16%Often: 13%Always: 7%

J. Johnson, XP2002

Software Engineering, lecture 8: Process vs Agile 26

Requirements in practice, the agile view

Realistic approach, based on 200+ SW projects:

Requirements always change Developers get complete specifications only 5%

of the times On average, design starts with 58%

requirements specified in detail

From: D. Reinertsen, S. Thomke: Agile Product Development: Managing Development Flexibility in Uncertain Environments, in California Management Review, Vol. 41, No. 1, Fall 1998, pp. 8-30.

Software Engineering, lecture 8: Process vs Agile 27

Evolutionary requirements analysis

Do we need to know all the functional requirements to start building a good core architecture?

Agile answer: the architect needs most nonfunctional or quality requirements (e.g. load, internationalization, response time) and a subset of functional requirements

Software Engineering, lecture 8: Process vs Agile 28

User stories

Software Engineering, lecture 8: Process vs Agile 29

Test-Driven Development: basic cycle

1. Add a test2. Run all tests and check the new one fails3. Implement code to satisfy functionality4. Check that new test succeeds5. Run all tests again to avoid regression6. Refactor code

After Kent Beck*

*Test Driven Development: By Example, Addison-Wesley

Software Engineering, lecture 8: Process vs Agile 30

TDD: a first assessment

For: Central role to tests Need to ensure that all

tests pass Continuous execution

But: Tests are not specs Risk that program pass

tests and nothing else

Stay tuned…

Software Engineering, lecture 8: Process vs Agile 31

Scrum practices

Self-directed and self-organizing teams of max 7 people

No external addition of work to an iteration, once chosen

Daily team measurement via a stand-up meeting called “scrum meeting”

30 calendar-day iterations Demo to stakeholders after each iteration

Software Engineering, lecture 8: Process vs Agile 32

Scrum lifecycle

Planning

Staging

Development

Release

Software Engineering, lecture 8: Process vs Agile 33

Scrum lifecycle: planning

Purpose: Establish the vision Set expectation Secure funding

Activities: Write vision Write budget Write initial product backlog Estimate items Exploratory design and prototypes

Software Engineering, lecture 8: Process vs Agile 34

Scrum lifecycle: staging

Purpose: Identify more requirements and prioritize

enough for first iteration

Activities: Planning Exploratory design and prototypes

Software Engineering, lecture 8: Process vs Agile 35

Sample product backlogRequirement N. Category Status Pri Est.(hrs)

log credit payments to AR

17 feature underway

5 2

process sale cash scenario

97 use case underway

5 60

slow credit payment approval

12 issue not started

4 10

sales commission calculation

43 defect complete

4 2

lay-away plan payments 88 enhance not started

3 20

PDA sale capture 53 technology

not started

1 100

process sale c.c. scenario 71 use case underway

5 30

C. Larman Agile & Iterative Development A Manager guide Addison Wesley 2003

Software Engineering, lecture 8: Process vs Agile 36

Scrum lifecycle: development & release

Software Engineering, lecture 8: Process vs Agile 37

XP practices: about people

Team typically works in an open space.

Stakeholders are mostly available

Every developer chooses his tasks (iteration planning game)

Pair programming

No overtime (sustainable pace)

Documentation: reduced to bare minimum

Software Engineering, lecture 8: Process vs Agile 38

XP lifecycle

Exploration

Planning

Iterations to first release

Productizing

Maintenance

Software Engineering, lecture 8: Process vs Agile 39

XP lifecycle: exploration

Purpose: Enough well-estimated user stories for first

release Feasibility ensured

Activities: Prototypes Exploratory proof of technology programming Story card writing and estimating

Software Engineering, lecture 8: Process vs Agile 40

XP lifecycle: planning

Purpose: Agree on date and stories of first release

Activities: Release planning game Story card writing and estimating

Software Engineering, lecture 8: Process vs Agile 41

XP lifecycle: iterations to first release

Purpose: Implement a tested system ready for release

Activities: Testing and programming Iteration planning game Task writing and estimating

Software Engineering, lecture 8: Process vs Agile 42

XP lifecycle: productizing

Purpose: Operational deployment

Activities: Documentation Training Marketing

Software Engineering, lecture 8: Process vs Agile 43

XP lifecycle: maintenance

Purpose: Enhance, fix Build major releases

Activities: May include this phases again, for

incremental releases

Software Engineering, lecture 8: Process vs Agile 44

What about tools?

Try to keep things as simple as possible

Only if they really help productivity and information sharing

Ideal situation: one relatively simple tool that seamlessly embraces all software lifecycle

Examples: No tool (white board + camera or video), Eiffelstudio, IBM Jazz project

Software Engineering, lecture 8: Process vs Agile 45

Agile methods links

www.agilealliance.comwww.cetus-links.orgwww.xprogramming.comwww.gilb.comwww.craiglarman.comwww.controlchaos.comwww.pols.co.uk/agile-zone/papers.htmlwww.eiffelroom.com

Software Engineering, lecture 8: Process vs Agile 46

Not everyone is gaga about XP

Software Engineering, lecture 8: Process vs Agile 47

Criticisms of XP

Hype not backed by evidence of success Loony ideas

(e.g. pair programming) “What’s good is not new, what’s new is not good” Rejection of proven software engineering

techniques Lack of design

(disdained in favor of refactoring) Lack of documentation

(disdain of “big upfront requirements”) Unfairly favors developer over customer Complicates contract negotiations

Software Engineering, lecture 8: Process vs Agile 48

Pair programming criticism

“Pair programming is necessary in XP because it compensates for a couple of practices that XP shuns: up-front-design and permanent documentation.

It makes up for the fact that the programmers are (courageously) making up the design as they code”.

(Stephens & Rosenberg)*

*Slightly abridged

(Ron Jeffries: “I think maybe concentration is the enemy. Seriously. If you’re working on something that is so complex that you actually need to concentrate, there’s too much chance that it’s too hard”)

Software Engineering, lecture 8: Process vs Agile 49

At first (Stephens & Rosenberg)

Software Engineering, lecture 8: Process vs Agile 50

“None of this actually matters” (Stephens & Rosenberg)

Software Engineering, lecture 8: Process vs Agile 51

The cycle (Stephens & Rosenberg)

Software Engineering, lecture 8: Process vs Agile 52

Contract-Driven Development

CDD = TDD — WTC*

Use contracts as specifications and test oracles

*Writing Test Cases

Andreas Leitnerwith Arno Fiva

(ETH)

53

Specified but unimplemented routine

54

Running the system and entering input

54

(erroneou

s)

55

The error is flagged at run time as a contract violation

55

56

This has become a test case

56

57

Another execution, another error

57

58

This has become a second test case

58

59

Editing the class

59

60

Correcting an error

60

61

Recompiling

61

62

Test cases are run again silently in the background

62

6363

One bug corrected, the other not

64

Attempting a fix

64

65

Still doesn’t work

65

66

We fix this (or think so)

66

67

The guardian angel is, however, watching

67

68

They fixed the bugs, had many children and lived happy ever after

68

Software Engineering, lecture 8: Process vs Agile 69

- 2 -

Process-based approaches:

RUP

Software Engineering, lecture 8: Process vs Agile 70

Rational Unified Process (RUP)

Process model designed by Rational (now IBM) on basis of Spiral model (Boehm) Objectory (Jacobson)

Software Engineering, lecture 8: Process vs Agile 71

RUP practices

Risk-driven requirements handling using use cases

Visual modelling

Develop in short timeboxed iterations

Focus on component architectures

Continuous measurement of quality factors

Up to 50 artifacts, all optional

Software Engineering, lecture 8: Process vs Agile 72

RUP: sample disciplines and artifacts

Discipline Artifact (Workproduct)Requirements Vision

Use-Case Model

Design Design model

Software Architecture Document

Project Management Iteration Plan

Risk List

C. Larman Agile & Iterative Development A Manager guide Addison Wesley 2003

Software Engineering, lecture 8: Process vs Agile 73

RUP lifecycle

Inception

Elaboration

Construction

Transition

Software Engineering, lecture 8: Process vs Agile 74

RUP phases

Software Engineering, lecture 8: Process vs Agile 75

- 3 -

The good, the bad and the ugly

Software Engineering, lecture 8: Process vs Agile 76

Retain from XP

Principles: Iterative development Customer involvement Support for change Primacy of code Self-organizing teams Technical excellence Search for simplicity

Practices: Evolutionary

requirements Customer on site User stories Pair programming Design & code standards Test-driven development Continuous testing Continuous refactoring Continuous integration Timeboxing (where

appropriate) Risk-driven development Daily tracking Servant-style manager

Software Engineering, lecture 8: Process vs Agile 77

Discard from XP

Pair programming as an imposed practiceRefusal to guarantee both functionality and delivery

dateTests as a substitute for specifications

Software Engineering, lecture 8: Process vs Agile 78

Retain against XP

Key software engineering practices: Extensive requirements process Documentation Upfront design Specifications as subsuming tests Role of manager Commitment to both functionality and date Design for generality

Software Engineering, lecture 8: Process vs Agile 79

Retain from process-based approaches

Engineering principlesDocumentationIdentification of tasksIdentification of task dependencies

Software Engineering, lecture 8: Process vs Agile 80

Reject from process-based approaches

Strict separation between analysis, design, implementation

Ignorance of the central role of change in software

Use cases as the principal source of requirements

Tendency to “Big Bang” effect

Software Engineering, lecture 8: Process vs Agile 81

The contribution of object technology

Focus on abstractions

Reuse (consumer and producer)

Seamless development

Reversibility

Single Model principle: The software is the

model The model is the

software The software includes

everything relevant to the project

Tools automatically extract views

See B. Meyer, PracticeTo Perfect:The Quality First Model, IEEE Computer, May 1997, pages 102-106, also at se.ethz.ch/~meyer/publications/computer/quality_first.pdf

(“Primacy” of code, but in a more far-reaching sense than in plain XP)

Contracts as a guide to analysis, design, implementation, maintenance, management

Continuous testing based on contracts

8282

Seamless development with Eiffel & contracts

Single notation, tools, concepts, principles

Continuous, incremental development

Keep model, implementation, documentation consistent

Reversibility

Example classes:PLANE, ACCOUNT, TRANSACTION…

STATE, COMMAND…

HASH_TABLE…

TEST_DRIVER…

TABLE…

Analysis

Design

Implemen-

tation

V&V

Generali-zation

83

Software Engineering

The cluster model

Cluster 1Cluster 2A

D

I

V&V

G

AD

I

V&V

G

AD

I

V&V

G

AD

I

V&V

G

84

Software Engineering

The cluster model

I

V

D

S

GI

V

D

S

GI

V

D

S

G

Cluster 1Cluster 2

I

V

D

S

G

Cluster n

I

V

D

S

G

I

V

D

S

G

85

Software Engineering

Cluster model: focus & practices

Clusters (set of related classes) Start with foundational clusters Mini lifecycles, each covering a cluster Seamlessness Reversibility Design by contract Current showable demo at every stage

86

Software Engineering

Mini-lifecycle tasks

Specification Design / Implementation Verification & Validation Generalization

87

Software Engineering

Mini-lifecycle tasks: specification

Identification of the data abstractions (classes) of the cluster

Identification of constraints (class invariants)

88

Software Engineering

Mini-lifecycle tasks: design & implementation

Definition of the class architecture Interface features Contracts

Definition of the relationships between classes Client Inheritance

Finalization of classes

89

Software Engineering

Mini-lifecycle tasks: verification & validation

Static examination

(Possibly) automated unit testing

90

Software Engineering

Mini-lifecycle tasks: generalization

Goal: turn classes in potentially reusable software components via:

Abstracting

Factoring

Documenting

91

Software Engineering

Generalization

Prepare for reuse. For example: Remove built-in limits Remove dependencies on

specifics of project Improve documentation,

contracts... Abstract Extract commonalities and

revamp inheritance hierarchy

Few companies have the guts to provide the budget for this

B

A*

Y

X

Z

A D I V G

92

Software Engineering

Software engineering principles

Quality pays

Architecture

Extendibility

Reusability

Reliability